Abstract The Gulf of Alaska experienced extreme temperatures during 2014–2019, including the four warmest years ever observed. The goal of this study is to evaluate the ecological consequences of that warming event, across multiple trophic levels and taxa. We tested for evidence that observed sea surface temperature (SST) anomalies were outside the envelope of natural climate variability in order to evaluate the risk of novel ecosystem configurations. We also tested for state changes in shared trends of climate (n = 11) and biology (n = 48) time series, using a Bayesian implementation of Dynamic Factor Analysis (DFA). And we tested for evidence of novel ecological relationships during 2014–2019. We found that 3-year running mean SST anomalies during 2014–2019 were outside the range of anomalies from preindustrial simulations in CMIP5 models, indicating that the combined magnitude and duration of the warming event was outside the range of natural variability. A DFA model of climate variability also returned a shared trend in climate time series that was at unprecedented levels during 2014–2019. However, DFA models fit to biology data did not show shared trends of variability at unprecedented levels, and Hidden Markov Models fit to shared trends from the climate and biology models failed to find evidence of shifts to a new ecosystem state during 2014–2019. Conversely, we did find preliminary indications that community responses to SST variability strengthened during 2014–2019 after decades of a mostly neutral relationship. Tests for nonstationary patterns of shared variability suggest that covariance between SST and other ecologically-important climate variables remained weaker than during the 1970s Pacific Decadal Oscillation shift, suggesting the potential for muted ecological responses to the 2014–2019 event. Finally, we found that recent patterns of community variability appear to be highly dissimilar to those associated with the 1970s event, suggesting the potential for novel community states with continued warming. In summary, we find no evidence for wholesale ecosystem reorganization during 2014–2019, though nonstationary relationships among climate and community variables suggest the ongoing possibility of novel patterns of ecosystem functioning with continued warming.

中文翻译：

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随着阿拉斯加湾温度超过工业化前可变性的极限，评估生态系统变化

摘要 阿拉斯加湾在 2014 年至 2019 年期间经历了极端温度，包括有史以来观察到的四个最温暖的年份。这项研究的目标是评估该变暖事件在多个营养级和分类群中的生态后果。我们测试了观察到的海面温度 (SST) 异常超出自然气候变化范围的证据，以评估新生态系统配置的风险。我们还使用动态因子分析 (DFA) 的贝叶斯实现测试了气候 (n = 11) 和生物学 (n = 48) 时间序列共享趋势的状态变化。我们在 2014-2019 年期间测试了新生态关系的证据。我们发现 2014-2019 年的 3 年平均 SST 异常超出了 CMIP5 模型中工业化前模拟的异常范围，表明变暖事件的综合幅度和持续时间超出了自然变异的范围。气候变率的 DFA 模型还返回了气候时间序列的共同趋势，该趋势在 2014-2019 年期间处于前所未有的水平。然而，适用于生物学数据的 DFA 模型并未显示出前所未有的变异趋势，而适用于气候和生物学模型共享趋势的隐马尔可夫模型未能找到 2014-2019 年向新生态系统状态转变的证据。相反，我们确实发现初步迹象表明，经过几十年的基本中性关系后，社区对 SST 变异性的反应在 2014-2019 年期间得到加强。对共享变异的非平稳模式的测试表明，海温与其他生态重要气候变量之间的协方差仍然比 1970 年代太平洋年代际振荡转变期间更弱，这表明对 2014-2019 事件的生态响应可能会减弱。最后，我们发现最近的群落变异模式似乎与 1970 年代事件相关的模式高度不同，这表明可能出现持续变暖的新群落状态。总而言之，我们没有发现 2014-2019 年期间生态系统大规模重组的证据，尽管气候和社区变量之间的非平稳关系表明，随着持续变暖，生态系统功能的新模式持续存在的可能性。表明可能对 2014-2019 年的事件产生温和的生态反应。最后，我们发现最近的群落变异模式似乎与 1970 年代事件相关的模式高度不同，这表明可能出现持续变暖的新群落状态。总而言之，我们没有发现 2014-2019 年期间生态系统大规模重组的证据，尽管气候和社区变量之间的非平稳关系表明，随着持续变暖，生态系统功能的新模式持续存在的可能性。表明对 2014-2019 年事件的生态反应可能会减弱。最后，我们发现最近的群落变异模式似乎与 1970 年代事件相关的模式高度不同，这表明可能出现持续变暖的新群落状态。总而言之，我们没有发现 2014-2019 年期间生态系统大规模重组的证据，尽管气候和社区变量之间的非平稳关系表明，随着持续变暖，生态系统功能的新模式持续存在的可能性。